Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 13 of 13 for “"Functional regression"”.
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Functional Regression and Adaptive Control
The author proposes a novel functional regression method for parameter estimation and adaptive control in this dissertation. In the functional regression method, the regressors and a signal which contains the information of the unknown parameters are either determined from raw measurements or …
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Sparse functional regression models: minimax rates and contamination
In functional linear regression and functional generalized linear regression models, the effect of the predictor function is usually assumed to be spread across the index space. In this dissertation we consider the sparse functional linear model and the sparse functional generalized linear models …
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Functional regression models in the frame work of reproducing kernel Hilbert space
… thesis is to systematically investigate some functional regression models for accurately quantifying the effect of functional predictors. In particular, three functional models are studied: functional linear regression model, functional Cox model, and function-on-scalar model. Both theoretical …
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Effect of Evapotranspiration Rate on Almond Yield in California
… (drought condition years). Model 1 determined a functional regression between almond yield and annual evapotranspiration during the 4 years of the study. The R<sup>2</sup>was 7.9%, meaning low association between both variables and high unexplained variability (92.1%). Model 2 evaluated year to …
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Adaptive Functional Data Analysis
… thesis, we contribute to adaptive modeling of functional data, focusing on the fundamental aspects of representation and regression, where challenges arise from the infinite-dimensionality of their underlying spaces. For adaptive representation, the notion of mixture inner product spaces (MIPS) …
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Bayesian analysis of historical functional linear models with application to air pollution forecasting
Historical functional linear models are used to analyse the relationship between a functional response and a functional predictor whereby only the past of the predictor process can affect the current outcome. In this work, we develop a Bayesian framework for the analysis of the historical …
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Functional linear regression on Namibian and South African data
… between geographically spate populations with functional regression analysis using climate variables at each location. A number of statistical challenges present themselves such as the multivariate nature of the data. Functional data analysis was used in this project to display the data so as …
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Theories and Experiments of Cognitive Knowledge Bases for Machine Learning
… cluster classification, pattern recognition, functional regression, behavior generation, and knowledge acquisition. Most current machine learning techniques fall into the first five categories. However, the sixth category of knowledge learning as humans do has remained as a fundamental problem …
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An investigation into Functional Linear Regression Modeling
Functional data analysis, commonly known as FDA", refers to the analysis of information on curves of functions. Key aspects of FDA include the choice of smoothing techniques, data reduction, model evaluation, functional linear modeling and forecasting methods. FDA is applicable in numerous …
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Shape curve analysis using curvature
… There is much recent literature in the area of functional regression where a scalar response can be related to a functional predictor. A novel approach for relating shape to a scalar response using functional regression, with curvature functions as predictors, is discussed and illustrated by a …
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Investigating functional data with sharp local features with applications to spectroscopy
… new methodology in the context of nonparametric functional statistics. The method has a sound theoretical background as it fully takes into account three cutting-edge statistical concepts: the nature of functional data, the nonparametric functional regression technique and unbalanced Haar …